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Senior C++ Systems Engineer (GPU Virtualization)

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Join a systems engineering team building software for GPU virtualization and cloud infrastructure, developing low-level C++ systems that improve GPU utilization. You will develop and maintain the core C++ virtualization library, research GPU oversubscription and checkpointing, extend hardware support, and debug and trace performance issues in production. Requires at least 3 years of C++ systems engineering experience with deep C++ expertise and production experience with low-level systems such as OS, kernels, memory management, or drivers.

Key Highlights
Low-level C++ systems for GPU virtualization and cloud infrastructure
On-site in San Francisco, CA
Base salary $250,000–$325,000 annually
Visa sponsorship available
At least 3 years of C++ systems engineering experience required
Key Responsibilities
Develop and maintain the core C++ virtualization library.
Research GPU oversubscription, checkpointing, and high-performance systems.
Extend support for new hardware architectures across the software stack.
Debug systems issues in production environments.
Trace performance problems across the stack and diagnose them in customer workloads.
Technical Skills Required
C++ Systems Programming Performance Optimization
Benefits & Perks
Visa sponsorship available
Nice to Have
Rust experience
Background in compilers, networking protocols, kernels, Kubernetes, infrastructure, distributed systems, storage, or data ingestion

Job Description

About the Role

Join a systems engineering team building software for GPU virtualization and cloud infrastructure. You will develop and optimize low-level C++ systems that improve GPU utilization for demanding computing workloads.

What You'll Do

  • Develop and maintain the core C++ virtualization library.
  • Research GPU oversubscription, checkpointing, and high-performance systems.
  • Extend support for new hardware architectures across the software stack.
  • Debug systems issues in production environments.
  • Trace performance problems across the stack and diagnose them in customer workloads.

What We're Looking For

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